{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Illinois Death Demographics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import utils\n",
    "import pandas as pd\n",
    "from datetime import date\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IDPH only publishes death demographics on and after 3/28, earlier entries (36 deaths) needs manual input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>County</th>\n",
       "      <th>Count</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age_bracket</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-03-17</td>\n",
       "      <td>Cook</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>60.0</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>Will</td>\n",
       "      <td>1</td>\n",
       "      <td>male</td>\n",
       "      <td>40.0</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>Cook</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>80.0</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>Sangamon</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>70.0</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-20</td>\n",
       "      <td>Cook</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>70.0</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date    County  Count     Sex  Age_bracket  \\\n",
       "0 2020-03-17      Cook      1  female         60.0   \n",
       "1 2020-03-19      Will      1    male         40.0   \n",
       "2 2020-03-19      Cook      1  female         80.0   \n",
       "3 2020-03-19  Sangamon      1  female         70.0   \n",
       "4 2020-03-20      Cook      1  female         70.0   \n",
       "\n",
       "                                           Reference  \n",
       "0  http://www.dph.illinois.gov/news/public-health...  \n",
       "1  http://www.dph.illinois.gov/news/public-health...  \n",
       "2  http://www.dph.illinois.gov/news/public-health...  \n",
       "3  http://www.dph.illinois.gov/news/public-health...  \n",
       "4  http://www.dph.illinois.gov/news/public-health...  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "manual_entries = utils.IL_death_demographic_early()  # check manual entries\n",
    "manual_entries.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## parse_IL_death_demographic combines manual early entry and later automatic parser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Automatic pdb calling has been turned ON\n"
     ]
    }
   ],
   "source": [
    "%pdb on"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-04-29 00:00:00  Requesting Page: 0\n",
      "2020-04-18 00:00:00  Requesting Page: 1\n",
      "2020-04-08 00:00:00  Requesting Page: 2\n",
      "2020-03-31 00:00:00  Requesting Page: 0\n"
     ]
    }
   ],
   "source": [
    "to_date = date.today()\n",
    "result = utils.parse_IL_death_demographic(pd.date_range('2020-02-01', to_date))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>County</th>\n",
       "      <th>Count</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age_bracket</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Lake</td>\n",
       "      <td>1</td>\n",
       "      <td>male</td>\n",
       "      <td>40</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Kankakee</td>\n",
       "      <td>1</td>\n",
       "      <td>male</td>\n",
       "      <td>50</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Kane</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>90</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Jefferson</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>90</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-04-28</td>\n",
       "      <td>Cook</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>20</td>\n",
       "      <td>http://www.dph.illinois.gov/news/public-health...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date     County  Count     Sex Age_bracket  \\\n",
       "24 2020-04-28       Lake      1    male          40   \n",
       "23 2020-04-28   Kankakee      1    male          50   \n",
       "22 2020-04-28       Kane      1  female          90   \n",
       "20 2020-04-28  Jefferson      1  female          90   \n",
       "0  2020-04-28       Cook      1  female          20   \n",
       "\n",
       "                                            Reference  \n",
       "24  http://www.dph.illinois.gov/news/public-health...  \n",
       "23  http://www.dph.illinois.gov/news/public-health...  \n",
       "22  http://www.dph.illinois.gov/news/public-health...  \n",
       "20  http://www.dph.illinois.gov/news/public-health...  \n",
       "0   http://www.dph.illinois.gov/news/public-health...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv('../outputs/death_demographic_' + str(to_date) + '.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivot = pd.pivot_table(result, index='Age_bracket', columns='Sex', values='Count', aggfunc='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x271c43c5438>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pivot.plot.bar(stacked=True, figsize=(10, 6), grid=True, title='IL Coronavirus Death Demographics as of 4/15/2020')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24577a95dd8>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pivot_ts = pd.pivot_table(result, index='Date', values='Count', aggfunc='sum')\n",
    "pivot_ts.plot(y='Count', style='*-', grid=True, title='Daily Death Count', figsize=(10,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Prepare for Flourish.studio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "total = result['Count'].sum()\n",
    "pivot = pivot.rename(columns={'female': 'female count', 'male': 'male count', 'unknown': 'unknown count'})\n",
    "pivot['female'] = pivot['female count'] / total * 100\n",
    "pivot['male'] = pivot['male count'] / total * 100\n",
    "pivot['unknown'] = pivot['unknown count'] / total * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sex</th>\n",
       "      <th>female count</th>\n",
       "      <th>male count</th>\n",
       "      <th>unknown count</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "      <th>unknown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_bracket</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.079302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.079302</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.317209</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.475813</td>\n",
       "      <td>1.506741</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>15.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.189532</td>\n",
       "      <td>2.854877</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>26.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.061856</td>\n",
       "      <td>6.740682</td>\n",
       "      <td>0.079302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>91.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.216495</td>\n",
       "      <td>11.022998</td>\n",
       "      <td>0.475813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>130.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.309278</td>\n",
       "      <td>15.226011</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>149.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.816019</td>\n",
       "      <td>14.115781</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>96.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.613006</td>\n",
       "      <td>4.599524</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.713719</td>\n",
       "      <td>0.317209</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unknown</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.079302</td>\n",
       "      <td>1.110230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Sex          female count  male count  unknown count     female       male  \\\n",
       "Age_bracket                                                                  \n",
       "0                     NaN         NaN            1.0        NaN        NaN   \n",
       "10                    1.0         NaN            NaN   0.079302        NaN   \n",
       "20                    NaN         4.0            NaN        NaN   0.317209   \n",
       "30                    6.0        19.0            NaN   0.475813   1.506741   \n",
       "40                   15.0        36.0            NaN   1.189532   2.854877   \n",
       "50                   26.0        85.0            1.0   2.061856   6.740682   \n",
       "60                   91.0       139.0            6.0   7.216495  11.022998   \n",
       "70                  130.0       192.0            NaN  10.309278  15.226011   \n",
       "80                  149.0       178.0            NaN  11.816019  14.115781   \n",
       "90                   96.0        58.0            NaN   7.613006   4.599524   \n",
       "100                   9.0         4.0            NaN   0.713719   0.317209   \n",
       "unknown               NaN         1.0           14.0        NaN   0.079302   \n",
       "\n",
       "Sex           unknown  \n",
       "Age_bracket            \n",
       "0            0.079302  \n",
       "10                NaN  \n",
       "20                NaN  \n",
       "30                NaN  \n",
       "40                NaN  \n",
       "50           0.079302  \n",
       "60           0.475813  \n",
       "70                NaN  \n",
       "80                NaN  \n",
       "90                NaN  \n",
       "100               NaN  \n",
       "unknown      1.110230  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivot.to_csv('../outputs/death_demographic_' + str(to_date) + '_flourish.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "\n",
    "link = 'https://coronavirus.illinois.gov/s/county-map'\n",
    "#headers = requests.utils.default_headers()\n",
    "#headers.update({ 'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:52.0) Gecko/20100101 Firefox/52.0'})\n",
    "req = requests.get(link)\n",
    "soup = BeautifulSoup(req.content, 'html.parser')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<script>\n",
       "     document.write('<style>');\n",
       " \tdocument.write('a.header {font-size: 20px; margin-right: 32px;}');\n",
       "     document.write('</style>');\n",
       " \n",
       "     document.write('<div class=\"header-email-line\" align=\"right\">');\n",
       " \n",
       "     document.write('<a class=header href=\"mailto:DPH.SICK@ILLINOIS.GOV\" target=\"_top\">DPH.SICK@ILLINOIS.GOV</a>');\n",
       " \tdocument.write('</div>');\n",
       " </script>,\n",
       " <script data-src=\"/jslibrary/1585773144000/canvas/CanvasRendering.js\"></script>,\n",
       " <script data-src=\"/jslibrary/1585773144000/ui-analytics-reporting/EclairNG.js\"></script>,\n",
       " <script src=\"/s/sfsites/l/%7B%22mode%22%3A%22PROD%22%2C%22app%22%3A%22siteforce%3AcommunityApp%22%2C%22fwuid%22%3A%22kHqYrsGCjDhXliyGcYtIfA%22%2C%22loaded%22%3A%7B%22APPLICATION%40markup%3A%2F%2Fsiteforce%3AcommunityApp%22%3A%22jezy9eMvUqztJqL1PQNDdA%22%7D%2C%22apce%22%3A1%2C%22apck%22%3A%22XqIkx4nyJvDxX87Zu6rF7g%22%2C%22mlr%22%3A1%2C%22pathPrefix%22%3A%22%22%2C%22dns%22%3A%22c%22%2C%22ls%22%3A1%2C%22ct%22%3A1%7D/inline.js?aura.attributes=%7B%22schema%22%3A%22Published%22%2C%22brandingSetId%22%3A%224812c588-5c10-4a59-a2b6-5ac97d3ed350%22%2C%22authenticated%22%3A%22false%22%2C%22ac%22%3A%22%22%2C%22formFactor%22%3A%22LARGE%22%2C%22publishedChangelistNum%22%3A%22236%22%2C%22viewType%22%3A%22Published%22%2C%22themeLayoutType%22%3A%22Inner%22%2C%22language%22%3A%22en_US%22%2C%22isHybrid%22%3A%22false%22%2C%22pageId%22%3A%2298efbf07-916a-45ba-9924-863449cc82c0%22%7D\"></script>,\n",
       " <script src=\"/s/sfsites/l/%7B%22mode%22%3A%22PROD%22%2C%22app%22%3A%22siteforce%3AcommunityApp%22%2C%22fwuid%22%3A%22kHqYrsGCjDhXliyGcYtIfA%22%2C%22loaded%22%3A%7B%22APPLICATION%40markup%3A%2F%2Fsiteforce%3AcommunityApp%22%3A%22jezy9eMvUqztJqL1PQNDdA%22%7D%2C%22apce%22%3A1%2C%22apck%22%3A%22XqIkx4nyJvDxX87Zu6rF7g%22%2C%22mlr%22%3A1%2C%22pathPrefix%22%3A%22%22%2C%22dns%22%3A%22c%22%2C%22ls%22%3A1%2C%22ct%22%3A1%7D/resources.js?pv=1585999354000&amp;rv=1586029220000\"></script>,\n",
       " <script src=\"/s/sfsites/auraFW/javascript/kHqYrsGCjDhXliyGcYtIfA/aura_prod_compat.js\"></script>,\n",
       " <script src=\"/s/sfsites/l/%7B%22mode%22%3A%22PROD%22%2C%22app%22%3A%22siteforce%3AcommunityApp%22%2C%22serializationVersion%22%3A%221-1.1.13-224.8-b%22%2C%22split%22%3A%22f%22%2C%22loaded%22%3A%7B%22APPLICATION%40markup%3A%2F%2Fsiteforce%3AcommunityApp%22%3A%22jezy9eMvUqztJqL1PQNDdA%22%7D%2C%22dns%22%3A%22c%22%2C%22ls%22%3A1%2C%22ct%22%3A1%7D/app.js\"></script>,\n",
       " <script src=\"/s/sfsites/l/%7B%22mode%22%3A%22PROD%22%2C%22app%22%3A%22siteforce%3AcommunityApp%22%2C%22fwuid%22%3A%22kHqYrsGCjDhXliyGcYtIfA%22%2C%22loaded%22%3A%7B%22APPLICATION%40markup%3A%2F%2Fsiteforce%3AcommunityApp%22%3A%22jezy9eMvUqztJqL1PQNDdA%22%7D%2C%22apce%22%3A1%2C%22apck%22%3A%22XqIkx4nyJvDxX87Zu6rF7g%22%2C%22mlr%22%3A1%2C%22pathPrefix%22%3A%22%22%2C%22dns%22%3A%22c%22%2C%22ls%22%3A1%2C%22ct%22%3A1%7D/bootstrap.js?aura.attributes=%7B%22schema%22%3A%22Published%22%2C%22brandingSetId%22%3A%224812c588-5c10-4a59-a2b6-5ac97d3ed350%22%2C%22authenticated%22%3A%22false%22%2C%22ac%22%3A%22%22%2C%22formFactor%22%3A%22LARGE%22%2C%22publishedChangelistNum%22%3A%22236%22%2C%22viewType%22%3A%22Published%22%2C%22themeLayoutType%22%3A%22Inner%22%2C%22language%22%3A%22en_US%22%2C%22isHybrid%22%3A%22false%22%2C%22pageId%22%3A%2298efbf07-916a-45ba-9924-863449cc82c0%22%7D\"></script>]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "soup.find_all('script')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<script>\n",
       "    document.write('<style>');\n",
       "\tdocument.write('a.header {font-size: 20px; margin-right: 32px;}');\n",
       "    document.write('</style>');\n",
       "\n",
       "    document.write('<div class=\"header-email-line\" align=\"right\">');\n",
       "\n",
       "    document.write('<a class=header href=\"mailto:DPH.SICK@ILLINOIS.GOV\" target=\"_top\">DPH.SICK@ILLINOIS.GOV</a>');\n",
       "\tdocument.write('</div>');\n",
       "</script>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "soup.script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[345, 0, 0, 0, 0, 0, 0, 0]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[len(l.text) for l in soup.find_all('script')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "for elm in soup.find_all('script'):\n",
    "    print('Cook' in elm.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Cook' in str(ll)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'ab' in 'abcd'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
